针对常规自对准中数据挖掘不充分问题,提出了一种基于逆向导航的捷联自对准方法。该方法首先对粗对准阶段的惯组数据进行存储,然后利用逆向导航算法,实现了存储数据的二次利用,最后采用卡尔曼滤波完成精对准。仿真表明,与常规自对准方法相比,新方法提高了惯组数据的利用率,缩短了对准时间。 Aiming at the problem of insufficient data mining in conventional self-alignment, a method of strapdown self-alignment based on reverse navigation is proposed. The method firstly stores the data of the habitual group in the coarse alignment stage, and then uses the reverse navigation algorithm to realize the secondary use of the stored data. Finally, the Kalman filter is used to finish the fine alignment. The simulation shows that the new method improves the utilization of the data of the habitual group and shortens the alignment time compared with the conventional self-alignment method.